RAMIN BOHLOULI

PhD Student

PhD program:: XXXIX
email: ramin.bohlouli@uniroma1.it
phone: +393471399267
building: DICEA - via Eudossiana, 18 - 00184 Roma Edificio A - Piano 3° - Area Trasporti
room: L008

supervisor: Prof. Guido Gentile

Ramin Bohlouli is a PhD student at Sapienza University of Rome, focusing on discrete choice analysis and demand prediction in the field of transportation. His research integrates advanced methodologies—including machine learning algorithms and large language models (LLMs)—to enhance mobility systems.

He has a solid background in software development with C# and is also familiar with Python and JavaScript. He is well‐versed in modern software engineering practices such as version control, CI/CD pipelines, and database management using PostgreSQL and MongoDB. His technical expertise is complemented by hands‐on experience with leading transportation engineering tools, including ArcGIS for spatial analysis and PTV Visum and Vissim for traffic simulation and modeling. He combines technical fluency with a strong passion for data‐driven, sustainable transport innovation.

Research products

11573/1749120 - 2025 - Enhancing Mode-Choice Models with Conformal Prediction: Uncertainty Quantification and Decision Support using Tree-Based Machine Learning

Bohlouli, Ramin; Varghese, Ken Koshy; Gentile, Guido; Eldafrawi, Mohamed - 01a Articolo in rivista

paper: TRANSPORT AND TELECOMMUNICATION (Warszawa: Versita Online-De Gruyter publishing group) pp. - - issn: 1407-6179 - wos: (0) - scopus: (0)

11573/1749100 - 2025 - Eco-routing in dense urban networks: evaluating time and emission trade-offs using the COPERT model in Rome

Pourkhosro, Siavash; Varghese, Ken Koshy; Bresciani Miristice, Lory Michelle; Bohlouli, Ramin; Gentile, Guido; Pedico, Valerio; Carrarini, Simone - 04b Atto di convegno in volume

conference: 9th IEEE Conference on Models and Technologies for Intelligent Transportation Systems, 2025 (Luxembourg; Luxembourg)

book: Proceedings of the 9th IEEE Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS 2025) - ()